1 citations · 1 across the 10 of their papers we have counts for
11 papers
Breaking Safety at the Token Boundary: How BPE Tokenization Creates Exploitable Gaps in LLM Alignment
Tung-Ling Li, Hongliang Liu, Yuhao Wu
Character-level perturbations bypass safety alignment in modern LLMs despite leaving prompts human-readable. We identify and test a central structural mechanism: BPE tokenization f…
Perturbation Probing: A Two-Pass-per-Prompt Diagnostic for FFN Behavioral Circuits in Aligned LLMs
Hongliang Liu, Tung-Ling Li, Yuhao Wu
Perturbation probing generates task-specific causal hypotheses for FFN neurons in large language models using two forward passes per prompt and no backpropagation, followed by a on…
Lost in Stories: Consistency Bugs in Long Story Generation by LLMs
Junjie Li, Xinrui Guo, Yuhao Wu +3
What happens when a storyteller forgets its own story? Large Language Models (LLMs) can now generate narratives spanning tens of thousands of words, but they often fail to maintain…
From Perception to Action: An Interactive Benchmark for Vision Reasoning
Yuhao Wu, Maojia Song, Yihuai Lan +8
Understanding the physical structure is essential for real-world applications such as embodied agents, interactive design, and long-horizon manipulation. Yet, prevailing Vision-Lan…
SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models
Yuhao Wu, Yushi Bai, Zhiqiang Hu +2
Long-form text generation remains a significant challenge for large language models (LLMs), particularly in maintaining coherence, ensuring logical consistency, and preserving text…
LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning
Yuhao Wu, Yushi Bai, Zhiqiang Hu +2
Ultra-long generation by large language models (LLMs) is a widely demanded scenario, yet it remains a significant challenge due to their maximum generation length limit and overall…
Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
Ziyu Ge, Yuhao Wu, Daniel Wai Kit Chin +2
Large Language Models (LLMs) augmented with retrieval mechanisms have demonstrated significant potential in fact-checking tasks by integrating external knowledge. However, their re…
Shifting Long-Context LLMs Research from Input to Output
Yuhao Wu, Yushi Bai, Zhiqing Hu +4
Recent advancements in long-context Large Language Models (LLMs) have primarily concentrated on processing extended input contexts, resulting in significant strides in long-context…
LongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models
Shangqing Tu, Yucheng Wang, Daniel Zhang-Li +8
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k visual and text tokens, yet they struggle to generate coherent outputs beyond 1,000…
AdaMCoT: Rethinking Cross-Lingual Factual Reasoning through Adaptive Multilingual Chain-of-Thought
Weihua Zheng, Xin Huang, Zhengyuan Liu +7
Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models show strong reasoning abilities, their pe…
LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs
Yuhao Wu, Ming Shan Hee, Zhiqing Hu +1
Current benchmarks like Needle-in-a-Haystack (NIAH), Ruler, and Needlebench focus on models' ability to understand long-context input sequences but fail to capture a critical dimen…